CVE-2026-19000 JeecgBoot CVE debrief

Who should care

Organizations using JeecgBoot up to 3.9.2, particularly those with exposed /airag/chat/send endpoints, should be aware of this vulnerability and take steps to mitigate potential risks. This includes reviewing deployments, applying compensating controls, and preparing for the upcoming fix. Security teams and vulnerability management teams should prioritize this vulnerability due to its potential impact and public exploit availability.

Technical summary

CVE-2026-19000 is a server-side request forgery vulnerability in JeecgBoot up to 3.9.2. The vulnerability affects the Anonymous Chat Attachment Parser component, specifically in the /airag/chat/send file. It allows remote exploitation, potentially leading to unauthorized server actions. The CVSS score is 5.5, indicating medium severity. A fix is planned for the upcoming release, but the exploit is publicly available. Organizations should prioritize patching and implement compensating controls.

Defensive priority

Organizations using JeecgBoot up to 3.9.2 should prioritize patching the Anonymous Chat Attachment Parser vulnerability to prevent potential server-side request forgery attacks.

Recommended defensive actions

• Inventory and verify affected JeecgBoot installations up to version 3.9.2
• Apply compensating controls to detect and prevent anomalous requests to sensitive resources
• Monitor for and respond to potential exploitation attempts
• Implement additional security measures to restrict access to the /airag/chat/send endpoint
• Review and apply vendor patch guidance when available
• Conduct exposure review for JeecgBoot deployments
• Track changes and verify source integrity for JeecgBoot

Evidence notes

The CVE-2026-19000 record indicates a server-side request forgery vulnerability in JeecgBoot up to 3.9.2, specifically in the /airag/chat/send file of the Anonymous Chat Attachment Parser component. The attack can be initiated remotely and a fix is planned for the upcoming release. However, details are limited, and further verification is necessary to fully understand the vulnerability's impact.

Sources and references

Methodology and review provenance

AI-assisted synthesis based on stored public vulnerability evidence. System validation, approval state, and publication status do not by themselves establish human review of this revision. PatchSiren helps prioritize defensive review and does not prove exposure or remediation on any system.